GoKawiilEssay traces how computer science's definition of 'efficient' lost sight of practical problems
A blog post on argmin examines the history of attempts to formally define algorithmic efficiency in computer science, starting with Jack Edmonds' 1965 paper on finding maximum matchings in graphs. The piece argues that Edmonds struggled to find rigorous language for 'efficient' or 'good' algorithms, distinguishing them from brute-force approaches that scale exponentially with problem size, and that this gap spawned a field of complexity theory that drifted from real-world applications.
GoKawiil's interpretation of the reporting above, not reported fact.
The essay suggests this pattern—where solving an abstract mathematical puzzle becomes disconnected from the original applied problem—recurs throughout mathematics and computer science, potentially diverting research effort toward theoretical curiosities. This could serve as a cautionary framework for readers evaluating how academic fields define and chase formal rigor versus practical usefulness.
- Jack Edmonds' 1965 matching algorithm paper first grappled with defining 'efficient' computation.
- The essay frames complexity theory's formalization as emblematic of mathematics losing sight of original applied problems.
- The piece is a historical/opinion essay rather than a report of new research or product news.
Source: argmin.net — Ben Recht, 2026-10-31
Published there as: “Efficient algorithms, the Exponential Time Hypothesis, and losing the plot”
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